Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks-Reference-Cited by-同舟云学术

Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks

Author:

You Chaoqun¹^ORCID,Guo Kun²^ORCID,Yang Howard H.³^ORCID,Quek Tony Q. S.¹^ORCID

Affiliation:

1. Wireless Networks and Design Systems Group, Singapore University of Technology and Design, Tampines, Singapore

2. Chongqing Key Laboratory of Precision Optics, Chongqing Institute, East China Normal University, Chongqing, China

3. Zhejiang University/University of Illinois at UrbanaChampaign Institute, Zhejiang University, Haining, China

Funder

National Research Foundation, Singapore, and Infocomm Media Development Authority under its Future Communications Research and Development Programme

Shanghai Pujiang Program

Natural Science Foundation of Chongqing, China

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Zhejiang–Singapore Innovation and Artificial Intelligence (AI) Joint Research Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Link

Reference34 articles.

1. Robust federated learning in a heterogeneous environment;ghosh;arXiv 1906 06629,2019

2. Enabling large-scale federated learning over wireless edge networks;quang dinh;arXiv 2109 10489,2021

3. PyTorch: An imperative style, high-performance deep learning library;paszke;Proc Adv Neural Inf Process Syst (NeurIPS),2019

4. HeteroFL: Computation and communication efficient federated learning for heterogeneous clients;diao;arXiv 2010 01264,2020

5. Federated learning with non-IID data;zhao;arXiv 1806 00582,2018

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